Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio

C. S. Ee; K. S. Sim; V. Teh; F. F. Ting

doi:10.1109/ICORAS.2016.7872600

Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio

C. S. Ee, K. S. Sim, V. Teh, F. F. Ting

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

9 Citations (Scopus)

Abstract

Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.

Original language	English
Title of host publication	Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509062058
DOIs	https://doi.org/10.1109/ICORAS.2016.7872600
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Robotics, Automation and Sciences 2016 - Melaka, Malaysia Duration: 5 Nov 2016 → 6 Nov 2016 https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding (Proceedings)

Conference

Conference	International Conference on Robotics, Automation and Sciences 2016
Abbreviated title	ICORAS 2016
Country/Territory	Malaysia
City	Melaka
Period	5/11/16 → 6/11/16
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding (Proceedings)

Keywords

CT Brain Images
Mean of Greyscale Level to Standard Deviation Ratio
Stroke
Window Width

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10.1109/ICORAS.2016.7872600

Cite this

Ee, C. S., Sim, K. S., Teh, V., & Ting, F. F. (2016). Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio. In Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICORAS.2016.7872600

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title = "Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio",

abstract = "Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.",

keywords = "CT Brain Images, Mean of Greyscale Level to Standard Deviation Ratio, Stroke, Window Width",

author = "Ee, {C. S.} and Sim, {K. S.} and V. Teh and Ting, {F. F.}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; International Conference on Robotics, Automation and Sciences 2016, ICORAS 2016 ; Conference date: 05-11-2016 Through 06-11-2016",

year = "2016",

doi = "10.1109/ICORAS.2016.7872600",

language = "English",

booktitle = "Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding",

}

Ee, CS, Sim, KS, Teh, V & Ting, FF 2016, Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio. in Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016. IEEE, Institute of Electrical and Electronics Engineers, International Conference on Robotics, Automation and Sciences 2016, Melaka, Malaysia, 5/11/16. https://doi.org/10.1109/ICORAS.2016.7872600

Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio. / Ee, C. S.; Sim, K. S.; Teh, V. et al.
Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016. IEEE, Institute of Electrical and Electronics Engineers, 2016.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio

AU - Ee, C. S.

AU - Sim, K. S.

AU - Teh, V.

AU - Ting, F. F.

PY - 2016

Y1 - 2016

N2 - Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.

AB - Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.

KW - CT Brain Images

KW - Mean of Greyscale Level to Standard Deviation Ratio

KW - Stroke

KW - Window Width

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DO - 10.1109/ICORAS.2016.7872600

M3 - Conference Paper

AN - SCOPUS:85016954460

BT - Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - International Conference on Robotics, Automation and Sciences 2016

Y2 - 5 November 2016 through 6 November 2016

ER -

Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio

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Keywords

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